FelixHo/Text-Classification-Benchmark

文本分类基准测试

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/ 100
Emerging

This project provides a benchmark for text classification, helping you understand how different machine learning algorithms perform on a balanced dataset of Chinese news and academic texts. It takes pre-segmented Chinese text, each labeled with a category, and outputs performance metrics like precision, recall, and F1-score for various classification models. This tool is useful for data scientists or researchers who need to compare the effectiveness of different text classification approaches.

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Use this if you need a quick comparison of common text classification algorithms on Chinese text data, especially if you're working with news or academic content.

Not ideal if your data is in a language other than Chinese, not pre-segmented, or requires custom feature engineering or hyperparameter tuning beyond the default settings.

text-analysis natural-language-processing information-categorization machine-learning-evaluation
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 7 / 25
Maturity 16 / 25
Community 17 / 25

How are scores calculated?

Stars

25

Forks

9

Language

Python

License

MIT

Last pushed

Mar 29, 2018

Commits (30d)

0

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curl "https://pt-edge.onrender.com/api/v1/quality/nlp/FelixHo/Text-Classification-Benchmark"

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